Identification of Three Rheumatoid Arthritis Disease Subtypes by Machine Learning Integration of Synovial Histologic Features and RNA Sequencing Data.
Dana E OrangePhaedra AgiusEdward F DiCarloNicolas RobineHeather GeigerJackie SzymonifkaMichael McNamaraRyan CummingsKathleen M AndersenSerene MirzaMark FiggieLionel B IvashkivAlessandra B PernisCaroline S JiangMayu O FrankRobert B DarnellNithya LingampaliWilliam H RobinsonEllen Gravallesenull nullVivian P BykerkSusan M GoodmanLaura T DonlinPublished in: Arthritis & rheumatology (Hoboken, N.J.) (2018)
Gene expression analysis of RA and OA synovial tissue revealed 3 distinct synovial subtypes. These labels were used to generate a histologic scoring algorithm in which the histologic scores were found to be associated with parameters of systemic inflammation, including the erythrocyte sedimentation rate, CRP level, and autoantibody levels. Comparison of gene expression patterns to clinical features revealed a potentially clinically important distinction: mechanisms of pain may differ in patients with different synovial subtypes.